Approximation algorithms for solving cost observable Markov decision processes

Technical Report

Public Deposited

Citeable URL: https://ir.library.oregonstate.edu/concern/technical_reports/1544bq53f

Descriptions

Attribute Name	Values
Creator	Oregon State University. Dept. of Computer Science Bayer, Valentina
Abstract	"The specifi c problem addressed in this proposal is the development of good approximation algorithms for solving problems that have partial observability. The model we propose associates costs with obtaining information about the current state. We want to predict when and how much it is necessary to observe. We want to use our Cost Observable Markov Decision Process (COMDP) model to find good solutions for real-world problems ..."--Problem definition.
Resource Type	Research Paper
Date Available	2012-04-23T16:11:08+00:00
Date Issued	1999
Series	Technical report (Oregon State University. Department of Computer Science)
Subject	Markov processes Computer algorithms
Rights Statement	Copyright Not Evaluated
Publisher	Corvallis, OR : Oregon State University, Dept. of Computer Science
Peer Reviewed	No
Language	English [eng]
Replaces	http://hdl.handle.net/1957/28851

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